Northwestern experts weigh in on how ChatGPT has and will continue impact biomedical research, and how artificial intelligence can be used to support the advancement of science and medicine.
Integrating social determinants of health helped mitigate bias when predicting long-term outcomes for heart failure patients, according to a Northwestern Medicine study.
In a new study, Northwestern investigators used artificial intelligence to analyze data from a wide variety of tissues, and discovered that the length of genes can explain most molecular-level changes that occur during aging.
The Institute for Artificial Intelligence in Medicine (I.AIM) has established the Center for Collaborative AI in Healthcare, with the mission of advancing artificial intelligence science, engineering and translation throughout healthcare specialties and create a positive impact on precision medicine.
Northwestern basic scientists are leveraging artificial intelligence and machine learning to untangle complex intracellular processes.
Northwestern investigators have developed a deep learning-based method that can predict cognitive function capacity based on brain shape and structure, detailed in a study published in Scientific Reports.
Northwestern Medicine and Google are collaborating on a project to bring fetal ultrasound to developing countries by combining AI (artificial intelligence), low-cost hand-held ultrasound devices and a smartphone.
Shifting machine learning workflows to a proactive model could speed data collection and analysis, according to a viewpoint published in JAMA.
A new anatomy curriculum for the MD and PA programs integrates the HoloAnatomy software, which allows students to visualize every part of the body through a virtual, three-dimensional perspective.
A machine learning model can identify patients at risk of a rare cardiomyopathy, according to a recent study.